Tooby and Cosmides received the 2020 Jean-Nicod Prize, “awarded annually to a leading philosopher of mind or philosophically-oriented cognitive scientist”
For details and the lectures visit here.
Tooby and Cosmides received the 2020 Jean-Nicod Prize, “awarded annually to a leading philosopher of mind or philosophically-oriented cognitive scientist”
For details and the lectures visit here.
Dan Conroy-Beam receives 2022-2023 Harold J. Plous Award for most outstanding young professor. See https://www.news.ucsb.edu/2022/020694/outstanding-performance
CEP graduate Michael Barlev won the 2018 New Investigator Award from the Human Behavior and Evolution Society for his work on “How the mind builds evolutionarily new concepts”. You can read the manuscript here: https://link.springer.com/article/10.3758/s13423-017-1421-6
Dan Conroy-Beam wins National Science Foundation’s Early Career Award, 2019. It is a prestigious NSF-CAREER Award for his groundbreaking project “Using Computer Simulations to Understand Mate Choice”.
The choice of a romantic partner is the most significant decision most people make in their lifetimes. Who people love often affects where they live and work, with whom they have and raise children, who they call friends and family, how they spend their time and money, who celebrates their successes, and who supports them in times of need. As a result, the quality of romantic relationships broadly affects physical health, mental health, and financial success. Understanding how people form and maintain these important relationships is central to understanding human social behavior. It is also a clear means of improving human health, happiness, and well being. Yet gaining a deeper understanding of the romantic partner choice process, and the role it plays in human welfare, is one of the great challenges of social and behavioral science. Romantic relationships develop within complex social environments. They are influenced by interactions between individual preferences, competition between romantic rivals, and mutual attractions that change over time. Accounting for such complex and intricate social systems requires assessing multiple, intertwined processes that are difficult to measure and observe. This project approaches the problem by developing a new computer simulation technique. The aim is to apply this technique to accelerate progress in basic understanding of romantic partner choice.
This new technique (“couple simulation”) compares theories of mate selection on their ability to reconstruct actual romantic relationships within computer simulations. Couple simulation will advance progress in mate choice research by providing the first empirical metrics for comparing different models of human mate selection. The method will help address questions such as: (1) what precisely are the decision processes that connect abstract, ideal preferences to real mate choices? (2) how do these early mate choice decisions relate to longer-term relationship quality and dissolution? (3) is it possible to identify those who are likely to have a fulfilling and supportive relationship? In preliminary studies, this technique identifies accurate models of romantic partner choice and predicts romantic relationship quality. This project will further develop couple simulation by combining agent-based modeling with studies of committed romantic couples, of change and stability in romantic relationships over time, and of the dynamics of initial relationship formation. The scientific aim is to produce computational models that more accurately describe romantic partner choice and that can more effectively aid people in forming fulfilling relationships. The project will also provide training in computational methods for a diverse group of early-career researchers, and it will contribute a novel, validated tool for relationship science to continue building on these successes into the future.
This award reflects NSF’s statutory mission and has been deemed worthy of support through evaluation using the Foundation’s intellectual merit and broader impacts review criteria.